IEEE

An Efficient FPGA Implementation of Spiking Neural Networks for N-MNIST Classification

Spiking Neural Networks (SNNs) have emerged as a promising alternative to conventional Artificial Neural Networks (ANNs) due to their event-driven computation and potential for low-power processing.
Frontiers

Domain-aware domain–class adaptation network for motor execution to motor imagery EEG classification

Motor imagery (MI) is one of the most widely used paradigms in electroencephalogram (EEG)-based brain–computer interfaces (BCIs). In recent years, deep learning and transfer learning techniques have ...
IEEE

Neural Network-Based Approximation of Continuous Control Set MPC for the Primary Control of DERs in AC Microgrids

Abstract: This article presents the design and functional validation of deep neural network-based approximators for the control policy of constrained model predictive control applied to a distributed ...
CNN

CNN sues Perplexity over alleged AI copyright theft

CNN is suing Perplexity, accusing the AI company of unlawfully copying and distributing CNN’s content. Thursday’s lawsuit joins a long list of legal actions by publishers like The New York Times ...
Nature

Brain age prediction in generalized anxiety disorder using a convolutional neural network

Higher predicted brain age difference has been associated with several psychiatric disorders. Generalized anxiety disorder (GAD) is associated with markers of accelerated aging. In this study, we ...
Nature

The Brain Imaging and Neurophysiology Dataset of large-scale multimodal neural data

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors ...